Top Stories, Jul 9-15: Analyze a Soccer (Football) Game Using Tensorflow Object Detection and OpenCV; Does PCA really improve classification outcome?

[unable to retrieve full-text content]Also: The 4 Levels of Data Usage in Data Science; fast.ai Deep Learning Part 1 Complete Course Notes; What is Minimum Viable (Data) Product?; Cartoon: Data Scientist was the sexiest job of the 21st century until…; Text Mining on the Command Line
Original Post: Top Stories, Jul 9-15: Analyze a Soccer (Football) Game Using Tensorflow Object Detection and OpenCV; Does PCA really improve classification outcome?

Top June Stories: 5 Data Science Projects That Will Get You Hired in 2018; Data Lake – the evolution of data processing

[unable to retrieve full-text content]Also: Football World Cup 2018 Predictions: Germany vs Brazil in the final, and more; The 5 Clustering Algorithms Data Scientists Need to Know.
Original Post: Top June Stories: 5 Data Science Projects That Will Get You Hired in 2018; Data Lake – the evolution of data processing

Top June Stories: 5 Data Science Projects That Will Get You Hired in 2018; Data Lake – the evolution of data processing

[unable to retrieve full-text content]Also: Football World Cup 2018 Predictions: Germany vs Brazil in the final, and more; The 5 Clustering Algorithms Data Scientists Need to Know.
Original Post: Top June Stories: 5 Data Science Projects That Will Get You Hired in 2018; Data Lake – the evolution of data processing

Top Stories, Jun 25 – Jul 1: 5 Data Science Projects That Will Get You Hired in 2018; 30 Free Resources for Machine Learning, Deep Learning, NLP & AI

[unable to retrieve full-text content]Also: Top 20 Python Libraries for Data Science in 2018; Why Data Scientists Love Gaussian; How to Execute R and Python in SQL Server with Machine Learning Services; Explaining Reinforcement Learning: Active vs Passive; What’s the Difference Between Data Integration and Data Engineering?
Original Post: Top Stories, Jun 25 – Jul 1: 5 Data Science Projects That Will Get You Hired in 2018; 30 Free Resources for Machine Learning, Deep Learning, NLP & AI

Top Stories, Jun 25 – Jul 1: 5 Data Science Projects That Will Get You Hired in 2018; 30 Free Resources for Machine Learning, Deep Learning, NLP & AI

[unable to retrieve full-text content]Also: Top 20 Python Libraries for Data Science in 2018; Why Data Scientists Love Gaussian; How to Execute R and Python in SQL Server with Machine Learning Services; Explaining Reinforcement Learning: Active vs Passive; What’s the Difference Between Data Integration and Data Engineering?
Original Post: Top Stories, Jun 25 – Jul 1: 5 Data Science Projects That Will Get You Hired in 2018; 30 Free Resources for Machine Learning, Deep Learning, NLP & AI

Top Stories, Jun 18-24: Detecting Sarcasm with Deep Convolutional Neural Networks; The 5 Clustering Algorithms Data Scientists Need to Know

[unable to retrieve full-text content]Also: What is it like to be a machine learning engineer in 2018?; 7 Simple Data Visualizations You Should Know in R; Choosing the Right Metric for Evaluating Machine Learning Models – Part 2; Data Lake – the evolution of data processing
Original Post: Top Stories, Jun 18-24: Detecting Sarcasm with Deep Convolutional Neural Networks; The 5 Clustering Algorithms Data Scientists Need to Know

Top Stories, Jun 11-17: Data Lake – the evolution of data processing; Generating Text with RNNs in 4 Lines of Code

[unable to retrieve full-text content]Also: Cartoon: 5 Machine Learning Projects You Should Not Overlook, June 2018; FIFA World Cup Football and Machine Learning; The What, Where and How of Data for Data Science; Data Lake the evolution of data processing
Original Post: Top Stories, Jun 11-17: Data Lake – the evolution of data processing; Generating Text with RNNs in 4 Lines of Code

Top Stories, May 28 – Jun 3: 10 More Free Must-Read Books for Machine Learning and Data Science; A Beginners Guide to the Data Science Pipeline

[unable to retrieve full-text content]Also: Descriptive analytics, machine learning, and deep learning viewed via the lens of CRISP-DM; On the contribution of neural networks and word embeddings in NLP; Improving the Performance of a Neural Network; Python eats away at R
Original Post: Top Stories, May 28 – Jun 3: 10 More Free Must-Read Books for Machine Learning and Data Science; A Beginners Guide to the Data Science Pipeline

Top Stories, May 21-27: Python eats away at R: Top Software for Analytics & Data Science; ETL vs ELT: Considering the Advancement of Data Warehouses

[unable to retrieve full-text content]Also: Top 20 R Libraries for Data Science in 2018; Frameworks for Approaching the Machine Learning Process; Machine Learning Breaking Bad – addressing Bias and Fairness in ML models
Original Post: Top Stories, May 21-27: Python eats away at R: Top Software for Analytics & Data Science; ETL vs ELT: Considering the Advancement of Data Warehouses